Embodiments of the inventive subject matter generally relate to the field of evolutionary algorithm based simulations, and, more particularly, to optimizing seeding of evolutionary algorithm based simulations.
Evolutionary algorithms use biological techniques based on biological evolution, reproduction, mutation, recombination, and natural selection to find solutions to optimization problems. Simulations that implement evolutionary algorithms act upon populations, such that individuals in a population represent candidate solutions to an optimization problem. The candidate solutions are evaluated for fitness and the population “evolves” as successive generations of the population are selected/generated based on the biological techniques. As the population evolves, overall fitness of the population tends to increase. A solution to the optimization problem is found when the overall fitness of the population has reached a satisfactory level. Simulations based on evolutionary algorithms can perform well for finding solutions to problems in engineering, biology, economics, robotics, etc. because fitness evaluation functions can be tailored to fit the problems.